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Book Graphs in Biomedical Image Analysis  and Overlapped Cell on Tissue Dataset for Histopathology

Download or read book Graphs in Biomedical Image Analysis and Overlapped Cell on Tissue Dataset for Histopathology written by Seyed-Ahmad Ahmadi and published by Springer Nature. This book was released on 2024 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This LNCS conference volume constitutes the proceedings of the MICCAI Workshop GRAIL 2023 and MICCAI Challenge OCELOT 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, September 23, and October 4, 2023. The 9 full papers (GRAIL 2023) and 6 full papers (OCELOT 2023) included in this volume were carefully reviewed and selected from GRAIL 14 (GRAIL 2023) and 6 (OCELOT 2023) submissions. The conference GRAIL 2023 a wide set of methods and application and OCELOT 2023 focuses on the cover a wide range of methods utilizing tissue information for better cell detection, in the sense of training strategy, model architecture, and especially how to model cell-tissue relationships.

Book Histopathological Image Analysis

Download or read book Histopathological Image Analysis written by Gurcan and published by Wiley-Blackwell. This book was released on with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Shape Analysis in Medical Image Analysis

Download or read book Shape Analysis in Medical Image Analysis written by Shuo Li and published by Springer Science & Business Media. This book was released on 2014-01-28 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

Book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging  and Graphs in Biomedical Image Analysis

Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Graphs in Biomedical Image Analysis written by Carole H. Sudre and published by Springer Nature. This book was released on 2020-10-05 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

Book Information Processing in Medical Imaging

Download or read book Information Processing in Medical Imaging written by Alejandro Frangi and published by Springer Nature. This book was released on 2023-06-07 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 28th International Conference on Information Processing in Medical Imaging, IPMI 2023, which took place in San Carlos de Bariloche, Argentina, in June 2023. The 63 full papers presented in this volume were carefully reviewed and selected from 169 submissions. They were organized in topical sections as follows: biomarkers; brain connectomics; computer-aided diagnosis/surgery; domain adaptation; geometric deep learning; groupwise atlasing; harmonization; federated learning; image synthesis; image enhancement; multimodal learning; registration; segmentation; self supervised learning; surface analysis and segmentation.

Book Artificial intelligence  A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment

Download or read book Artificial intelligence A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment written by Mónica Hebe Vazquez-Levin and published by Frontiers Media SA. This book was released on 2023-04-26 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Medical Image Computing and Computer Assisted Intervention     MICCAI 2021

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2021 written by Marleen de Bruijne and published by Springer Nature. This book was released on 2021-09-23 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

Book Digital Pathology

    Book Details:
  • Author : Constantino Carlos Reyes-Aldasoro
  • Publisher : Springer
  • Release : 2019-07-03
  • ISBN : 3030239373
  • Pages : 192 pages

Download or read book Digital Pathology written by Constantino Carlos Reyes-Aldasoro and published by Springer. This book was released on 2019-07-03 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th European Congress on Digital Pathology, ECDP 2019, held in Warwick, UK in April 2019. The 21 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The congress theme will be Accelerating Clinical Deployment, with a focus on computational pathology and leveraging the power of big data and artificial intelligence to bridge the gaps between research, development, and clinical uptake.

Book Image Analysis in Histology

Download or read book Image Analysis in Histology written by Richard Wootton and published by CUP Archive. This book was released on 1995-05-11 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a timely and useful introduction to the theory and practical application of image analysis in histology. This powerful research technique can be used to detect not only stored products in a cell (immunocytochemistry) but the synthetic machinery and the genes that control it (in situ hybridisation), as well as the specific binding sites that act as receptors for a molecule following its release (in vitro autoradiography). The book provides a good introduction for beginners before looking in greater detail at more advanced material in selected areas. The volume highlights the importance of technique in gathering quantitative information. The book is divided into four sections: introductory material, image acquisition, image processing, and applications. The applications areas include quantitative immunochemistry, quantification of nerves and neurotransmitters and automated grain counting in in situ hybridisation histochemistry.

Book Deep Learning for Medical Image Analysis

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache

Book Biomedical Texture Analysis

Download or read book Biomedical Texture Analysis written by Adrien Depeursinge and published by Academic Press. This book was released on 2017-08-25 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements Describes, using intuitive concepts, how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different Identifies the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators Showcases applications where biomedical texture analysis has succeeded and failed Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis

Book Modern Techniques in Cytopathology

Download or read book Modern Techniques in Cytopathology written by M.M. Bui and published by Karger Medical and Scientific Publishers. This book was released on 2020-01-13 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of precision medicine, physicians are increasingly in need of more definitive diagnostic, prognostic, and predictive information derived from small biopsy specimens such as cytology samples in order to guide effective patient care. Cytopathology is well poised to meet this challenge. Whilst the traditional cytomorphologic component of cytology practice is still valid, enormous advances have been made in the field of cytopathology thanks to transformative technology and innovative individuals that have augmented the cytologists' ability to meet the demands of modern medicine. The purpose of this book is to describe, illustrate, and review many of the most recent developments regarding modern techniques employed in cytopathology. This latest monograph is intended for all cytologists including cytopathologists, cytotechnologists, cytology lab assistants, trainees, research scientists, and anyone who is interested in the field of cytopathology. We have invited pioneering experts in their respective fields to author these chapters. This book is not only the culmination of their groundbreaking work and effort but also presents a critical review of the current literature. We have attempted to provide readers with an informative and comprehensive aid so that they may better appreciate how emerging technology has been applied to cytology. Each chapter in this book presents a stand-alone contemporary review of emerging topics in cytopathology. We hope that you will find this monograph thought-provoking and a valuable reference for your practice.

Book From Ecology to Cancer Biology and Back Again

Download or read book From Ecology to Cancer Biology and Back Again written by Frederick R. Adler and published by Frontiers Media SA. This book was released on 2022-03-08 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Artificial Intelligence in Medical Imaging

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Book Deep Learning and Convolutional Neural Networks for Medical Image Computing

Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Book Proceedings of COMPSTAT 2010

Download or read book Proceedings of COMPSTAT 2010 written by Yves Lechevallier and published by Springer Science & Business Media. This book was released on 2010-11-08 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 19th international symposium on computational statistics, held in Paris august 22-27, 2010.Together with 3 keynote talks, there were 14 invited sessions and more than 100 peer-reviewed contributed communications.

Book Medical Image Computing and Computer Assisted Intervention     MICCAI 2017

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2017 written by Maxime Descoteaux and published by Springer. This book was released on 2017-09-03 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.